According to a new press release, “Indico, a provider of Enterprise AI solutions for intelligent process automation, today announced the launch of a new open source project focused on enhancing the performance of machine learning for natural language processing. Named Finetune, the project offers users a single, general-purpose language model which can be easily tuned to solve a variety of different tasks involved in text and document-based workflows. ‘Finetuning’ is a specific type of transfer learning designed to take a model trained on one task and adapt it to solve a different, but related task. Users can make small modifications to repurpose an existing model to effectively solve a new, related problem, saving substantial time and effort, while also improving accuracy. ‘Most organizations have natural language processing problems, but few have the labeled data they need to solve them with machine learning,’ said Madison May, Indico machine learning architect and cofounder. ‘Finetune lets them do more with less labeled training data. And it only requires a base level of IT experience’.”

The release goes on, “The Finetune project extends original research and development work completed by OpenAI to address a wider range of problems. OpenAI’s base project provides an illustrative model for increasing the accuracy and performance of machine learning models with natural language content and includes general capabilities for document classification, comparison, and multiple-choice question answering. The Finetune library packages that capability up for easier use and supports additional tasks such as document annotation, regression, and multi-label classification.”

Read more at Globe Newswire.

Photo credit: Indico